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Débute 4 June 2026 05:03
Se termine 4 June 2026
XG-Boost 101: Used Cars Price Prediction
2865 Cours
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Title:
XG-Boost 101:
Used Cars Price Prediction
Description:
Dive into the realm of machine learning with our hands-on project where you'll learn to predict used car prices using three different algorithms:
Multiple Linear Regression, Random Forest Regression, and XG-Boost. Ideal for car dealerships, this project will enhance your understanding of the factors influencing used car prices.
By the end of this project, participants will:
- Gain insights into the application of AI and Machine Learning in the automotive industry.
- Explore the theory and practical application of the XG-Boost Algorithm.
- Learn to import and use key Python libraries, manage datasets, and conduct Exploratory Data Analysis.
- Utilize data visualization tools like Seaborn, Plotly, and Word Cloud to interpret data better.
- Prepare data for modeling by standardizing and splitting into training and testing sets.
- Develop skills in building, training, and evaluating models with XG-Boost, Random Forest, and Multiple Linear Regression using Scikit-Learn.
- Assess model performance through various Key Performance Indicators (KPIs).
Note:
This course is optimized for learners in North America.
Efforts are underway to bring this learning experience to other regions.
Provider:
Coursera
Categories:
Artificial Intelligence Courses, Python Courses, Machine Learning Courses, scikit-learn Courses, Data Visualization Courses.
Enseigné par
Ryan Ahmed
